Privacy-Preserving Reengineeringof Model-View-Controller ApplicationArchitectures Using Linked Data

Abstract

When a legacy system's software architecture cannot be redesigned, implementing additional privacy requirements is often complex, unreliable and costly to maintain. This paper presents a privacy-by-design approach to reengineer web applications as linked data-enabled and implement access control and privacy preservation properties. The method is based on the knowledge of the application architecture, which for the Web of data is commonly designed on the basis of a model-view-controller pattern. Whereas wrapping techniques commonly used to link data of web applications duplicate the security source code, the new approach allows for the controlled disclosure of an application's data, while preserving non-functional properties such as privacy preservation. The solution has been implemented and compared with existing linked data frameworks in terms of reliability, maintainability and complexity.

A New Geometric Data Perturbation Method for Data Anonymization Based on Random Number Generators

“…With the acceleration of technological developments regarding collecting and storing such extensive data, data mining studies, which are the science of extracting meaningful information from data, have also gained importance [3]. In addition, it has become a new field of study that needs to be worked on to ensure the privacy of sensitive data about individuals and organizations in mining operations or in any area where data is accessible.…”